Study On Automatic Modulation Recognition Of Communication Signals

Automatic modulation recognition is one of the keys to uncooperative communication and software radio communication,and it plays a very important role in military and civilian fields.With the rapid development of modern communication technology and signal processing technology,the communication systems and the signal modulation types are becoming more and more complex.The automatic modulation recognition of communication signal is facing increasingly severe challenges because of the complex communication environment and the noise interference.How to improve the correct recognition rate of the signal under the low SNR conditions and limited symbols is an important research direction of modulation recognition in uncooperative communication.Firstly,this paper analyzes the modulation and demodulation principles of MPSK,MQAM and MAPSK signals,designs the modulation and demodulation algorithms,and calculates the high-order theoretical accumulation of different modulation types.Secondly,focusing on the problem of low signal recognition rate under low signal-to-noise ratio,the modulation recognition algorithm based on high-order cumulant is improved.First,the large frequency signal stochastic resonance system is used for preprocessing to improve the signal-to-noise ratio of the signal;and then the high-order cumulant characteristic parameters are extracted to realize the modulation type of the communication signal under low signal-to-noise ratio conditions.The effectiveness of the algorithm is verified by experimental simulations.Finally,for the problem of difficult signal modulation recognition when the number of symbols is limited in uncooperative communication,this paper makes two improvements in the modulation recognition algorithm based on wavelet transform: on the one hand,the inter-class recognition algorithm based on the variance feature of wavelet transform is improved.The fractal box dimension of the signal after wavelet transform is extracted to improve the correct recognition rate between MPSK signals and MQAM signals;on the other hand,the peaksearch algorithm is improved.The effective recognition of MPSK signals with limited symbols are achieved by extracting the phase difference characteristics after the wavelet transform,and the MQAM signals are recognized by the amplitude characteristics after the wavelet transform.The experimental results verify the effectiveness of inter-class recognition algorithm and in-class recognition algorithm.